Instructions to use circulus/nsfw_image with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use circulus/nsfw_image with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="circulus/nsfw_image") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("circulus/nsfw_image") model = AutoModelForImageClassification.from_pretrained("circulus/nsfw_image", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 89922c97180e791563557ab254ef656642d57637fdbd2a786e9df954a1ae7810
- Size of remote file:
- 687 MB
- SHA256:
- 02ff26c6fe3d23991889a373ee79cdb2ea615b3a04b65b1b5cf6985365edf414
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.